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        Download the raw data used to create the plots in this report below:

        Note that additional data was saved in multiqc_data when this report was generated.


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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        Tool Citations

        Please remember to cite the tools that you use in your analysis.

        To help with this, you can download publication details of the tools mentioned in this report:

        About MultiQC

        This report was generated using MultiQC, version 1.25.1

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        This report has been generated by the ebi-metagenomics/assembly-analysis-pipeline analysis pipeline. For information about how to interpret these results, please see the documentation.

        Report generated on 2025-05-28, 17:57 BST based on data in: /hps/nobackup/rdf/metagenomics/service-team/projects/mgnify-asa/work/mbc/17/a4bd452015c1bb7f8e9087b9138d25


        General Statistics

        Showing 0/2 rows and 2/2 columns.
        Sample NameN50 (Kbp)Assembly Length (Mbp)
        ERZ857107_filtered
        13.9Kbp
        1.3Mbp
        ERZ857107_renamed
        13.9Kbp
        1.3Mbp

        QUAST

        Quality assessment tool for genome assemblies.URL: http://quast.bioinf.spbau.ruDOI: 10.1093/bioinformatics/btt086

        Assembly Statistics

        Showing 0/2 rows and 4/4 columns.
        Sample NameN50 (Kbp)L50 (K)Largest contig (Kbp)Length (Mbp)
        ERZ857107_filtered
        13.9Kbp
        0.0K
        60.4Kbp
        1.3Mbp
        ERZ857107_renamed
        13.9Kbp
        0.0K
        60.4Kbp
        1.3Mbp

        Number of Contigs

        This plot shows the number of contigs found for each assembly, broken down by length.

        Created with MultiQC

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        GroupSoftwareVersion
        ANTISMASH_ANTISMASHantismash8.0.0
        antismash database8.0.0
        ANTISMASH_JSON_TO_GFFmgnify-pipelines-toolkit1.2.0
        ANTISMASH_SUMMARYmgnify-pipelines-toolkit1.0.5
        CATPACK_CONTIGScatpack6.0
        catpack database202501
        CMSEARCHTBLOUTDEOVERLAPcmsearch_tblout_deoverlapv0.09
        COMBINEDGENECALLER_MERGEmgnify-pipelines-toolkit1.2.0
        CONCATENATE_ANTISMASH_GBKpigz2.3.4
        CONCATENATE_ANTISMASH_GFFSpython3.13.1
        CONCATENATE_CMSEARCH_DEOVERLAPpigz2.3.4
        CONCATENATE_DBCAN_GFFSpython3.13.1
        CONCATENATE_DBCAN_HMMOUTcsvtk0.31.0
        CONCATENATE_DBCAN_OVERVIEWcsvtk0.31.0
        CONCATENATE_DBCAN_STANDARD_OUTcsvtk0.31.0
        CONCATENATE_DBCAN_SUBSTRATEScsvtk0.31.0
        CONCATENATE_EGGNOGMAPPER_ANNOTATIONSpigz2.3.4
        CONCATENATE_EGGNOGMAPPER_ORTHOLOGSpigz2.3.4
        CONCATENATE_HMMSEARCH_TBLOUTpigz2.3.4
        CONCATENATE_INTERPROSCAN_GFFSpython3.13.1
        CONCATENATE_INTERPROSCAN_TSVpigz2.3.4
        CONCATENATE_SANNTIS_GFFSpython3.13.1
        DBCANdbcan4.1.4
        dbcan database4.1.4-V13
        DIAMOND_BLASTPdiamond2.1.11
        DIAMOND_RHEACHEBIdiamond2.1.11
        mgnify-pipelines-toolkit0.2.1
        uniref90rhea database2025_01.2025-04-01.137
        DRAM_DISTILL_PER_ASSEMBLYdram1.3.5
        dram databases1.3.0
        DRAM_DISTILL_PER_SAMPLESHEETdram1.3.5
        dram databases1.3.0
        EASEL_ESLSFETCHeasel0.49
        EGGNOGMAPPER_ANNOTATIONSeggnog-mapper2.1.12
        eggnog-mapper database5.0.2
        EGGNOGMAPPER_ORTHOLOGSeggnog-mapper2.1.12
        eggnog-mapper database5.0.2
        EXTRACTCOORDSmgnify-pipelines-toolkit1.2.0
        FILTER_ASSEMBLYseqkitv2.8.0
        FRAGGENESCANRSFragGeneScanRs1.1.0
        GENERATEGAFmgnify-pipelines-toolkit1.2.0
        GENOMEPROPERTIESGenome Properties2.0
        GFF_SUMMARYmgnify-pipelines-toolkit1.2.0
        GT_GFF3VALIDATORgenometools1.6.5
        HMMSEARCH_KOFAMShmmer3.4
        kofam version202503
        INFERNAL_CMSEARCHRfam version15.0
        cmsearch1.1.5
        INTERPROSCANInterProScan5.73-104.0
        InterProScan database5.73-104.0
        INTERPRO_SUMMARYcsvtk0.31.0
        tabix1.21
        KEGGPATHWAYSCOMPLETENESSkegg-pathways-completeness1.3.0
        KEGG_ORTHOLOGS_SUMMARYbiopython1.85
        csvtk0.31.0
        tabix1.21
        KRONA_KTIMPORTTEXTkrona2.8.1
        MERGE_ANTISMASH_JSONjq1.5
        MGNIFYPIPELINESTOOLKIT_KRONATXTFROMCATCLASSIFICATIONmgnify-pipelines-toolkit1.2.0
        MGNIFYPIPELINESTOOLKIT_SUMMARISEGOSLIMSmgnify-pipelines-toolkit1.2.0
        OWLTOOLSgolism version20160705
        owltools2024-06-12T00:00:00Z
        PFAM_SUMMARYcsvtk0.31.0
        tabix1.21
        PYRODIGALpyrodigal3.6.3
        QUASTquast5.2.0
        RENAME_CONTIGSpyfastax2.2.0
        python3.9.21
        SANNTISSanntiS0.9.4.1
        SANNTIS_SUMMARYmgnify-pipelines-toolkit1.2.0
        SEQKIT_FIXcsvtk0.31.0
        SEQKIT_SEQ_BGCseqkitv2.9.0
        SEQKIT_SPLIT2seqkit2.8.0
        SUMMARISE_FOR_DRAM_INPUTpython3.13.0
        TABIX_BGZIP_GOtabix1.2
        TABIX_BGZIP_GOSLIMtabix1.2
        TABIX_BGZIP_KEGGPATHWAYSCOMPLETENESStabix1.2
        TABIX_BGZIP_KEGGPATHWAYSCOMPLETENESS_PER_CONTIGtabix1.2
        TABIX_BGZIP_RHEAANDCHEBItabix1.2
        WorkflowNextflow24.10.3
        ebi-metagenomics/assembly-analysis-pipelinev6.0.0-beta-g0859cda

        ebi-metagenomics/assembly-analysis-pipeline Methods Description

        Suggested text and references to use when describing pipeline usage within the methods section of a publication.URL: https://github.com/ebi-metagenomics/assembly-analysis-pipeline

        Methods

        Data was processed using ebi-metagenomics/assembly-analysis-pipeline v6.0.0-beta (doi: 10.1093/nar/gkac1080), this pipeline is part of EMBL-EBI's metagenomics platform.

        The pipeline was executed with Nextflow v24.10.3 (Di Tommaso et al., 2017) with the following command:

        nextflow run ebi-metagenomics/assembly-analysis-pipeline -r dev -latest -config /hps/software/users/rdf/metagenomics/service-team/configs/pipelines-nextflow-configs/configs/assembly-analysis-pipeline/codon.config -profile codon -resume --input /hps/nobackup/rdf/metagenomics/service-team/users/mbc/mgnify-asa/input/ERZ857107.csv --outdir results/ERZ857107 -with-tower

        The MGnify assembly analysis pipeline performs comprehensive annotation of metagenomic assemblies. The pipeline employs the Combined Gene Caller for coding sequence prediction (Richardson et al. 2022), followed by functional annotation using InterProScan for protein annotation (Jones et al. 2014), dbCAN for carbohydrate-active enzyme annotation (Zheng et al. 2023), and HMMER (Eddy 2011) for homology searches against the KEGG database (Aramaki 2019). Taxonomic classification is performed using CAT (von Meijenfeldt et al. 2019), while biosynthetic gene cluster identification is performed antiSMASH (Blin et al. 2021) and SanntiS (Sanchez et al. 2023). Additional tools support various pipeline functions, including Infernal for RNA homology searches (Nawrocki & Eddy 2013), QUAST for assembly quality assessment (Gurevich et al. 2013), and MultiQC for report aggregation (Ewels et al. 2016). Metabolic pathway analysis is performed with DRAM (Shaffer et al. 2020) and Genome Properties (Richardson et al. 2018), with visualization of the taxonomic annotations with with Krona (Ondov et al. 2011) and data processing facilitated by SeqKit (Shen et al. 2016), tabix (Li et al. 2009), FragGeneScanRs (Van der Jeugt et al. 2022), Pyrodigal (Larralde 2022), and Genome Tools (Gremme et al. 2013).

        References

        • Richardson L, Allen B, Baldi G, Beracochea M, Bileschi ML, Burdett T, et al. MGnify: the microbiome sequence data analysis resource in 2023 [Internet]. Vol. 51, Nucleic Acids Research. Oxford University Press (OUP); 2022. p. D753–9. doi: 10.1093/nar/gkac1080
        • Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., & Notredame, C. (2017). Nextflow enables reproducible computational workflows. Nature Biotechnology, 35(4), 316-319. doi: 10.1038/nbt.3820
        • Ewels, P. A., Peltzer, A., Fillinger, S., Patel, H., Alneberg, J., Wilm, A., Garcia, M. U., Di Tommaso, P., & Nahnsen, S. (2020). The nf-core framework for community-curated bioinformatics pipelines. Nature Biotechnology, 38(3), 276-278. doi: 10.1038/s41587-020-0439-x
        • Grüning, B., Dale, R., Sjödin, A., Chapman, B. A., Rowe, J., Tomkins-Tinch, C. H., Valieris, R., Köster, J., & Bioconda Team. (2018). Bioconda: sustainable and comprehensive software distribution for the life sciences. Nature Methods, 15(7), 475–476. doi: 10.1038/s41592-018-0046-7
        • da Veiga Leprevost, F., Grüning, B. A., Alves Aflitos, S., Röst, H. L., Uszkoreit, J., Barsnes, H., Vaudel, M., Moreno, P., Gatto, L., Weber, J., Bai, M., Jimenez, R. C., Sachsenberg, T., Pfeuffer, J., Vera Alvarez, R., Griss, J., Nesvizhskii, A. I., & Perez-Riverol, Y. (2017). BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics (Oxford, England), 33(16), 2580–2582. doi: 10.1093/bioinformatics/btx192
        • Richardson, L., Allen, B., Baldi, G., Beracochea, M., Bileschi, M. L., Burdett, T., et al. (2022). MGnify: the microbiome sequence data analysis resource in 2023. Nucleic Acids Research, 51, D753–D759. doi: 10.1093/nar/gkac1080
        • Richardson, L. J., Rawlings, N. D., Salazar, G. A., Almeida, A., Haft, D. R., Ducq, G., et al. (2018). Genome properties in 2019: a new companion database to InterPro for the inference of complete functional attributes. Nucleic Acids Research, 47, D564–D572. doi: 10.1093/nar/gky1013
        • Buchfink, B., Reuter, K., & Drost, H. G. (2021). Sensitive protein alignments at tree-of-life scale using DIAMOND. Nature Methods, 18, 366–368. doi: 10.1038/s41592-021-01101-x
        • Nawrocki, E. P., & Eddy, S. R. (2013). Infernal 1.1: 100-fold faster RNA homology searches. Bioinformatics, 29, 2933–2935. doi: 10.1093/bioinformatics/btt509
        • Ondov, B. D., Bergman, N. H., & Phillippy, A. M. (2011). Interactive metagenomic visualization in a Web browser. BMC Bioinformatics, 12, 385. doi: 10.1186/1471-2105-12-385
        • Larralde, M. (2022). Pyrodigal: Python bindings and interface to Prodigal, an efficient method for gene prediction in prokaryotes. Journal of Open Source Software, 7, 4296. doi: 10.21105/joss.04296
        • Zheng, J., Ge, Q., Yan, Y., Zhang, X., Huang, L., & Yin, Y. (2023). dbCAN3: automated carbohydrate-active enzyme and substrate annotation. Nucleic Acids Research, 51, W115–W122. doi: 10.1093/nar/gkad328
        • Jones, P., Binns, D., Chang, H. Y., Fraser, M., Li, W., McAnulla, C., et al. (2014). InterProScan 5: genome-scale protein function classification. Bioinformatics, 30, 1236–1240. doi: 10.1093/bioinformatics/btu031
        • von Meijenfeldt, F. A. B., Arkhipova, K., Cambuy, D. D., Coutinho, F. H., & Dutilh, B. E. (2019). Robust taxonomic classification of uncharted microbial sequences and bins with CAT and BAT. Genome Biology, 20, 217. doi: 10.1186/s13059-019-1817-x
        • Van der Jeugt, F., Dawyndt, P., & Mesuere, B. (2022). FragGeneScanRs: faster gene prediction for short reads. BMC Bioinformatics, 23, 198. doi: 10.1186/s12859-022-04736-5
        • Sanchez, S., Rogers, J. D., Rogers, A. B., Nassar, M., McEntyre, J., Welch, M., et al. (2023). Expansion of novel biosynthetic gene clusters from diverse environments using SanntiS. bioRxiv. doi: 10.1101/2023.05.23.540769
        • Shaffer, M., Borton, M. A., McGivern, B. B., Zayed, A. A., La Rosa, S. L., Solden, L. M., et al. (2020). DRAM for distilling microbial metabolism to automate the curation of microbiome function. Nucleic Acids Research, 48, 8883–8900. doi: 10.1093/nar/gkaa621
        • Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., et al. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25, 2078–2079. doi: 10.1093/bioinformatics/btp352
        • Blin, K., Shaw, S., Kloosterman, A. M., Charlop-Powers, Z., van Wezel, G. P., Medema, M. H., & Weber, T. (2021). antiSMASH 6.0: improving cluster detection and comparison capabilities. Nucleic Acids Research, 49(W1), W29–W35. doi: 10.1093/nar/gkab335
        • Eddy, S. R. (2011). Accelerated Profile HMM Searches. PLoS Computational Biology, 7, e1002195. doi: 10.1371/journal.pcbi.1002195
        • Gurevich, A., Saveliev, V., Vyahhi, N., & Tesler, G. (2013). QUAST: quality assessment tool for genome assemblies. Bioinformatics, 29, 1072–1075. doi: 10.1093/bioinformatics/btt086
        • Shen, W., Le, S., Li, Y., & Hu, F. (2016). SeqKit: A Cross-Platform and Ultrafast Toolkit for FASTA/Q File Manipulation. PLOS ONE, 11, e0163962. doi: 10.1371/journal.pone.0163962
        • Gremme, G., Steinbiss, S., & Kurtz, S. (2013). GenomeTools: A Comprehensive Software Library for Efficient Processing of Structured Genome Annotations. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 10(3), 645–656. doi: 10.1109/TCBB.2013.68
        • Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics , 32(19), 3047–3048. doi: /10.1093/bioinformatics/btw354
        Notes:
        • The command above does not include parameters contained in any configs or profiles that may have been used. Ensure the config file is also uploaded with your publication!
        • You should also cite all software used within this run. Check the "Software Versions" of this report to get version information.

        ebi-metagenomics/assembly-analysis-pipeline Workflow Summary

        - this information is collected when the pipeline is started.URL: https://github.com/ebi-metagenomics/assembly-analysis-pipeline

        Input/output options

        input
        /hps/nobackup/rdf/metagenomics/service-team/users/mbc/mgnify-asa/input/ERZ857107.csv
        outdir
        results/ERZ857107

        Reference databases for the pipeline

        antismash_database
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/antismash/8.0.0
        cat_diamond_database
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/cattaxonomy/2025_01/db/
        cat_taxonomy_database
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/cattaxonomy/2025_01/tax
        dbcan_database
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/dbcan/4.1.4-V13/
        dram_databases
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/dram/1.3.0/
        eggnog_data_dir
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/eggnog/5.0.2/data
        eggnog_database
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/eggnog/5.0.2/data/eggnog.db
        eggnog_diamond_database
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/eggnog/5.0.2/data/eggnog_proteins.dmnd
        go_banding
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/goslim/20160705/metagenomics_go_slim_banding.txt
        go_obo
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/goslim/20160705/go-basic-metagenomics_release_20160705.obo
        goslim_ids
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/goslim/20160705/metagenomics_go_slim_ids.txt
        interpro_licensed_software
        true
        interproscan_database
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/interproscan/5.73-104.0
        ko_list_txt
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/kofam/2025_03/ko_list
        kofam_hmm_database
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/kofam/2025_03/kofam_modified.hmm
        rfam_claninfo
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/rfam/15.0/Rfam.clanin
        rfam_covariance_models
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/rfam/15.0/Rfam.cm
        rfam_version
        15.0
        rheachebi_mapping_tsv
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/uniref90rhea/2025_01.2025-04-01.137/rhea_chebi_mapping.tsv
        uniref90rhea_diamond_database
        /hps/nobackup/rdf/metagenomics/service-team/production/ref-dbs/mgnify-v6/asa/uniref90rhea/2025_01.2025-04-01.137/uniref90_rhea.dmnd
        uniref90rhea_diamond_database_version
        2025_01.2025-04-01.137

        Generic options

        trace_report_suffix
        2025-05-28_17-15-21

        Core Nextflow options

        configFiles
        N/A
        containerEngine
        singularity
        launchDir
        /hps/nobackup/rdf/metagenomics/service-team/users/mbc/mgnify-asa
        profile
        codon
        projectDir
        /homes/mbc/.nextflow/assets/ebi-metagenomics/assembly-analysis-pipeline
        revision
        dev
        runName
        shrivelled_crick
        userName
        mbc
        workDir
        /hps/nobackup/rdf/metagenomics/service-team/projects/mgnify-asa/work/mbc